An Overview of the MySQL Engine and its Latest Features
Google engEDU
54 min – Apr 26, 2006

Google TechTalks
April 26, 2006

Timour Katchaounov

ABSTRACT
The first part of this talk describes the main principles behind MySQL’s query optimizer and execution engine, how the optimizer transforms queries into executable query plans, what these plans look like, and how they are executed.

The second part of the talk describes the major improvements in the query engine of MySQL 5.0, and how these improvements can benefit the users of MySQL 5.0. The "greedy" optimizer reduces compilation time for big queries with orders of magnitude. The "index merge" access method provides a way to use more than one index for the same query. For faster plan execution and to allow better join orders, the 5.0 optimizer transforms most outer joins into inner joins.

The outer joins that cannot be transformed into inner ones are executed in a pipeline manner, so that no intermediate results need to be materialized. Finally, some GROUP BY and DISTINCT queries can be executed much faster thanks to "loose index scan" technique that reads only a fraction of an index.

The talk concludes with the near-future plans for new features coming in the next versions of MySQL.
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Internet Advertising and the Generalized Second Price Auction
Google engEDU
1 hr 3 min – Feb 9, 2006

Google TechTalks
February 9, 2006

Michael Schwarz

Michael Schwarz served as an Assistant Professor at Harvard Economics Department after earning a Ph.D. from Stanford Graduate School of Business. He is a member of the National Bureau of Economics Research. Dr. Schwarz specializes in economic theory and industrial organization and applications of theory to business decision making and public policy.

ABSTRACT
We investigate the "generalized second price" auction (GSP), a new mechanism which is used by search engines to sell online advertising that most Internet users encounter daily. GSP is tailored to its unique environment, and neither the mechanism nor the environment have previously been studied in the mechanism design literature. Although GSP looks similar to the Vickrey-Clarke-Groves (VCG) mechanism, its properties are very different. In particular, unlike the VCG mechanism, GSP generally does not have an equilibrium in dominant strategies, and truth-telling is not an equilibrium of GSP. To analyze the properties of GSP in a dynamic environment, we describe the generalized English auction that corresponds to the GSP and show that it has a unique equilibrium. This is an ex post equilibrium that results in the same payoffs to all players as the dominant strategy equilibrium of VCG.
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Should Google Go Nuclear? Clean, cheap, nuclear power (no, really)
Google engEDU
1 hr 33 min – Nov 9, 2006

Google Tech Talks
November 9, 2006

ABSTRACT
This is not your father’s fusion reactor! Forget everything you know about conventional thinking on nuclear fusion: high-temperature plasmas, steam turbines, neutron radiation and even nuclear waste are a thing of the past. Goodbye thermonuclear fusion; hello inertial electrostatic confinement fusion (IEC), an old idea that’s been made new. While the international community debates the fate of the politically-turmoiled $12 billion ITER (an experimental thermonuclear reactor), simple IEC reactors are being built as high-school science fair projects.

Dr. Robert Bussard, former Asst. Director of the Atomic Energy Commission and founder of Energy Matter Conversion Corporation (EMC2), has spent 17 years perfecting IEC, a fusion process that converts hydrogen and boron directly into electricity producing helium as the only waste product. Most of this work was funded by the Department of Defense, the details of which have been under seal… until now.

Dr. Bussard will discuss his recent results and details of this potentially world-altering technology, whose conception dates back as far as 1924, and even includes a reactor design by Philo T. Farnsworth (inventor of the scanning television).

Can a 100 MW fusion reactor be built for less than Google’s annual electricity bill? Come see what’s possible when you think outside the thermonuclear box and ignore the herd.
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Multiview Geometry for Texture Mapping 2D Images onto 3D Range Data
Google engEDU
46 min – Jun 29, 2006

Google TechTalks
June 29, 2006

George Wolberg

http://www-cs.engr.ccny.cuny.edu/~wolberg/

ABSTRACT
The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. In this talk, we describe a system that integrates multiview geometry and automated 3D registration techniques for texture mapping 2D images onto 3D range data. The 3D range scans and the 2D photographs are respectively used to generate a pair of 3D models of the scene. The first model consists of a dense 3D point cloud, produced by using a 3D-to-3D registration method that matches 3D lines in the range images. The second model consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs.

This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photo-realistic models with minimal human interaction. We present results from experiments in large-scale urban scenes.

Joint with with Prof. Ioannis Stamos, Lingyun Liu, Gene Yu, and Siavash Zokai.
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• [1] Multiview Geometry For Texture Mapping 2d Images Onto 3d Range Data

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DSD: A Hybrid Analysis Tool for Bug Finding
Google engEDU
42 min – Jul 13, 2006

Google TechTalks
July 13, 2006

Christoph Csallner

ABSTRACT
DSD-Crasher is a bug finding tool that follows a three-step approach to program analysis: D. Capture the program’s intended execution behavior with dynamic invariant detection. The derived invariants exclude many unwanted values from the program’s input domain. S. Statically analyze the program within the restricted input domain to explore many paths. D. Automatically generate test cases that focus on verifying the results of the static analysis. Thereby confirmed results are never false positives, as opposed to the high false positive rate inherent in conservative static analysis.

This three-step approach yields benefits compared to past two-step combinations in the literature. In our evaluation with third-party applications, we demonstrate higher precision over tools that lack a dynamic step and higher efficiency over tools that lack a static step.
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Seattle Conference on Scalability: Building a Scalable Resource Management
Google engEDU
56 min – Jun 23, 2007

Google Tech Talks
June 23, 2007

ABSTRACT

2007 Google Seattle Conference on Scalability: Building a Scalable Resource Mgmt System for Grid Computing
Speaker: Khalid Ahmed, Platform Computing Corp.

This talk will describe the architecture and implementation details
for building a highly scalable resource management layer that can
support a variety of applications and workloads. This technology
has evolved from large scale computing grids deployed in
production at customers such as Texas Instruments, AMD, JP
Morgan, and various government labs. We will show how to build a
centralized dynamic load information collection service that can
handle up to 5000 nodes/20,000 cpus in a single cluster. The
service is able to gather a variety of system level metrics and is
extensible to collect up to 256 dynamic or static attributes of a node
and actively feed them to a centralized master. A built-in election
algorithm ensures timely failover of the master service ensuring
high-availability without the need for specialized interconnects.
This building block is extended to multiple clusters that can be
organized hierarchically to support a single resource management
domain that can span multiple data centers. We believe the current
architecture could scale to 100,000 nodes/400,000 cpus. Additional
services such as a distributed process execution service, and a
policy-based resource allocation engine which leverage this core
scale-out clustering service are described. The protocols,
communication overheads, and various design tradeoffs that were
made the development of these services will be presented along
with experimental results from various tests, simulations and
production environments.
Khalid Ahmed works as the Chief Architect and Director of
Technology Research at Platform Computing. In over 12 years at
Platform he worked in a number of roles including development,
product management and architecture. His work on distributed
scheduling, wide-area resource sharing, workload management,
system automation, virtualization management, and high availability
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Motion Estimation from Image and Inertial Measurements
Google engEDU
56 min – Feb 24, 2006

Google TechTalks
February 24, 2006

Dennis Strelow

Robust motion from monocular image measurements would be an enabling technology for Mars rover, micro air vehicle, and search and rescue robot navigation; and for modeling complex environments from video.
While algorithms exist for estimating six degree of freedom motion from monocular image measurements, motion from image measurements suffers from inherent problems. These include sensitivity to incorrect or insufficient image feature tracking; sensitivity to camera modeling and calibration errors; and long-term drift in scenarios with missing observations, i.e., where image features enter and leave the field of view.
The integration of image and inertial measurements is an attractive solution to some of these problems. Among other advantages, adding inertial measurements to image-based motion estimation can reduce the sensitivity to incorrect image feature tracking and camera modeling errors. On the other hand, image measurements can be exploited to reduce the drift that results from integrating noisy inertial measurements; and allow the additional unknowns needed to interpret inertial measurements, such as the gravity direction and magnitude, to be estimated.
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PhotoSketch: A Photo-Centric 3D Modeling Tool
Google engEDU
56 min – Jun 26, 2007

Google Tech Talks
June 26, 2007

ABSTRACT

Geospatial navigation tools such as Google Earth and Microsoft Virtual Earth are exceedingly popular applications for exploring massive datasets. Their explosive growth provides impetus for photorealistic 3D modeling of urban scenes. Although laser range scanners are traditional sources for detailed 3D models of existing structures, the heavyweight models they generate are not appropriate for the streaming data that these navigation applications leverage. Instead, lightweight models as produced by photogrammetry tools are better suited for this domain. Unfortunately, photogrammetry tends to be a very labor-intensive operation, requiring manual camera calibration and tedious modeling processes. This talk presents the virtues of combining computer vision techniques and photogrammetry to simplify the 3D modeling workflow. The contribution of this work is that it merges the benefits of automatic feature extraction, multiview geometry, an intuitive sketching interface, and dynamic texture mapping to produce lightweight photorealistic 3D models of buildings. We present results from experiments in large-scale urban scenes.

Speaker: George Wolberg
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Navigating the World’s Photographs
Google engEDU
1 hr 1 min – Jun 13, 2007

Google Tech Talks
June 13, 2007

ABSTRACT

There’s a big difference between looking at a photograph of a place and being there. But what if you had access to every photo ever captured of that place and could conjure up any view at will? With billions of photographs currently available online, the Internet is beginning to resemble such a database, capturing most of the world’s significant sites from a huge number of vantage points and viewing conditions. For example, a Google image search for "notre dame" or "grand canyon" each returns more than half a million photos, showing the sites from myriad viewpoints, different times of day and night, and changes in season, weather and decade.

This talk explores ways of transforming this massive, unorganized photo collection into visualizations of the world’s sites, cities, and landscapes. After a brief recap of our work on Photo Tourism and Photosynth, I will focus on current efforts and newest results, in the domains of 3D scene reconstruction and new visual interfaces for navigating photo collections.
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The Theoretical Limits of Statistical High Dimensional Nearest Neighbor Algor…

55 min – Sep 6, 2007

Google Tech Talks
September 6, 2007

ABSTRACT

Suppose we have $n$ Bernoulli(1/2) long sequences of bits. Let $n-2m$ sequences be completely independent, while the remaining $2m$ sequences are composed of $m$ independent pairs. The interdependence within each pair is that their bits agree with probability $1/20$. The exponent $1/p$ is optimal in a large natural class of algorithms which we name Bucketing Codes. Moreover if one sequence out of each pair belongs to a known set of $n^{(2p-1)^{2}-epsilon}$ sequences, than pairing can be done using order $n$ comparisons!

These results are extended to a general discrete independent data model. The performance of Bucketing Codes is bounded by a newly defined Bucketing Information. That bound can be asymptotically attained by randomly constructed bucketing codes. Our Information Theory inspired approach is contrasted with the worst case analysis dominating the literature.

Speaker: Moshe Dubiner
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General Purpose, Low Power Supercomputing Using Reconfiguration
Google engEDU
56 min – Feb 28, 2006

Google TechTalks
February 28, 2006

Prof. Bob Brodersen

ABSTRACT:
The ability of FPGA technology to exploit the advances in IC fabrication technology has resulted in the present situation in which a FPGA computing fabric is the most power and area efficient approach for general purpose parallel computing. This has occurred because the Von-Neumann processor architectures are now power limited and can no longer fully exploit the technology advances (thus the move to multi-cores). Hardware composed of arrays of FPGA’s and memory has been design that achieves a TeraOp/second of performance per board with over an order of magnitude higher efficiency for the computation per unit power over conventional microprocessors. To achieve these results, however, requires a high level of parallelism in the application program, which is typically not exposed in sequential programming languages. Even worse for application programmers, has been the low level of abstraction of FPGA hardware, which requires the user to be a hardware expert. It is believed that for any application that can be parallelized and streamed will presently achieve orders of magnitude speed-up for the same power and cost and even more importantly will have a power efficiency which will improve exponentially in each subsequent IC technology node.
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Decision Making and Chance
Google engEDU
59 min – Sep 17, 2006

Google Tech Talks
September 17, 2006

Dr. Mike Orkin is a Managing Scientist at Exponent, a publicly traded scientific consulting company headquartered in Menlo Park. Mike has numerous research publications in game theory and probability theory and has written data mining and simulation software. He is a nationally known authority on odds and gambling games and has appeared on numerous TV and radio shows to discuss gambling and odds, including CNN, NBC’s Dateline and ABC’s World News Tonight.

ABSTRACT
Certain gambling games, such as roulette and craps, are games of pure chance: In repeated play, luck disappears, and the persistent gambler will go broke. Other gambling activities, such as betting on sports or the stock market, may involve an element of skill. One way to measure this is to compare the results of a gambling strategy with chance: A skillful strategy should produce long-run results that are better than would be achieved by someone who is just guessing. One can also compare a gambler’s losses with chance to see if the gambler is doing worse than chance would allow. I will discuss two recent projects that illustrate these concepts:

• Automated data mining software discovers that the Baltimore Ravens are 17-3 versus the point spread when they lost their previous game and their opponents played their previous game on the road. Do situations like this give clever gamblers an edge or are such strong win-loss records merely random flukes?

• A gambler loses $30 million betting at an online casino. Is it possible to lose this much just by chance or is the gambler being cheated? Or maybe the gambler is part of a money laundering scheme.
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Incremental Bayesian Networks for Natural Language Parsing
Google engEDU
1 hr 1 min – Aug 13, 2007

Google Tech Talks
August 13, 2007

ABSTRACT

Natural language parsing is a particularly challenging structure prediction problem, due to the large space of output structures and the complex nature of the statistical dependencies between features of the output structures. Typically these statistical dependencies are specified by hand, but recently there has been interest in using latent variables to induce them automatically. In this talk I will present a framework for structure prediction with latent variables based on a form of Dynamic Bayesian Network called Incremental Sigmoid Belief Networks (ISBNs), and illustrate how it can be applied to parsing. Approximations to ISBNs have achieved state-of-the-art results on Penn Treebank parsing and on dependency parsing for a variety of languages.

ISBNs are designed for non-Markovian problems such an parsing, where the structure of the statistical dependencies is a function of the output structure. Exact inference in ISBNs cannot be done efficiently (as with many complex graphical models), but they are designed to allow efficient approximations. Such approximations include my previous neural network architecture for statistical parsing, and an incremental mean field approximation. The mean field approximation demonstrates that a more accurate approximation does lead to a more accurate parser, but the neural network approximation is much faster and achieves close to the same accuracy.
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NASA’s "Beyond Einstein" Program: Exploration at the Limits of Space & Time

53 min – Aug 30, 2007

Google Tech Talks
August, 30 2007

ABSTRACT

Albert Einstein’s General Theory of Relativity predicted results that were so incredible that even he did not accept them: space is expanding from a Big Bang, space itself contains an energy that is pulling the Universe apart from within, and deep chasms of gravity called black holes actually exist. Astonishingly, all of these wild ideas are now known to be true. But now we need to build on Einstein’s work to take the next step — to study the underlying physics of the very phenomena that came out of his theories. NASA’s Beyond Einstein program consists of a series of space missions, large and small, that push Einstein’s theories to their limits, using increasingly more sensitive probes. The two flagship missions now in development, Constellation-X and LISA, will explore extremes of space, measuring X-rays and gravitational waves. The smaller missions, the Einstein probes, will target specific science questions such as "What is Dark Energy?" and "What powered the Big Bang?"

Speaker: Randall Smith
Randall Smith is an X-ray Astrophysicist at the Johns Hopkins University and NASA/Goddard Space Flight Center. He worked at the Chandra X-ray Center for six years after the launch of the Chandra X-ray Observatory before moving to JHU & NASA to work with the Suzaku X-ray Telescope. He is a member of the Cons…
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Scalability and Efficiency on Data Mining Applied to Internet Applications
Google engEDU
43 min – Aug 16, 2007

Google Tech Talks
August 16, 2007

ABSTRACT

The Internet went well beyond a technology artefact, increasingly becoming a social interaction tool. These interactions are usually complex and hard to analyze automatically, demanding the research and development of novel data mining techniques that handle the individual characteristics of each application scenario. Notice that these data mining techniques, similarly to other machine learning techniques, are intensive in terms of both computation and I/O, motivating the development of new paradigms, programming environments, and parallel algorithms that support scalable and efficient applications. In this talk we present some results that justify not only the need for developing these new techniques, as well as their parallelization.

Wagner Meira Jr. obtained his PhD from the University of Rochester in 1997 and is currently Associate Professor at the Computer Science Department at Universidade Federal de Minas Gerais, Brazil. His research focuses on scalability and efficiency of large scale parallel and distributed systems, from massively parallel to Internet-based platforms, and on data mining algorithms, their parallelization, and application to areas such as information retrieval, bioinformatics, and e-governance.
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Bay Area Discrete Math Day XII: Stat. Physics, Comp. Simulation, and Probability
Google engEDU
41 min – Apr 15, 2006

Google TechTalks
Bay Area Discrete Math Day XII
April 15, 2006

Raissa D’Souza (UC Davis)

ABSTRACT
Statistical physics, computer simulation and discrete mathematics are intimately related through the study of shared models. These are primarily lattice models, such as the Ising model, yet can also involve discrete structures such as networks. Several models illustrate the current interplay between these three fields, while also providing cautionary tales of interpolating results obtained in one realm to the other. This talk will survey several such models, focusing on pattern formation in a simple first-order jamming transition.
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7 Ways To Ruin A Technological Revolution
Google engEDU
1 hr 14 min – Dec 18, 2006

Google Tech Talks
December 18, 2006

ABSTRACT

If you wanted to undermine the technological revolution of the last 30 years, using the law, how would you do it? How would you undercut the virtuous cycle that results from access to an open network, force technological innovation into stagnation, diminish competition, create monopolies over the basic building blocks of knowledge? How many of those things are we doing now?

James Boyle is William Neal Reynolds Professor of Law at Duke Law School, the founder of the Center for the Study of the Public Domain, and a Board Member of Creative Commons. He is also a columnist for the Financial Times New Technology Policy Forum. His most recent books were Bound By Law — a comic book about fair use — and The Shakespeare Chronicles, a literary mystery about the authorship of Shakespeare’s works.
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Mysteries of the Human Genome
Google engEDU
1 hr 3 min – Oct 23, 2006

Google Tech Talks
October 23, 2006

Gill Bejerano holds a BSc, summa cum laude, in Mathematics, Physics, and Computer Science, and a PhD in Computer Science from the Hebrew University of Jerusalem, Israel. Twice recipient of the RECOMB best paper by a young scientist award, and a former Eshkol pre-doctoral Scholar and HHMI postdoc. As co-discoverer of ultraconserved elements, his research focuses on deciphering the function and evolution of the non-coding regions of the Human Genome. Gill is currently a postdoc with David Haussler at UC Santa Cruz, and in early 2007 he will join Stanford university as an Assistant Professor in the Department of Developmental Biology and the Department of Computer Science.

ABSTRACT
The human genome, the hereditary material we pass on to our progeny, can be cast as a 3 billion letter string over a DNA alphabet of four. We currently understand 1.5% of this mass, mostly in the form of genes, DNA substrings that code for proteins, the quintessential constituents of every living cell. The remainder 98.5% of our genome was often deemed as "junk". This picture changed when the genome of related species became available. By comparison we are suddenly able to pinpoint the locations of a staggering one million additional human subsequences that must be important to the human cell. The functions of these regions remain largely unknown, while their sheer volume overwhelms any comprehensive experimental approach. Guided by experimental results for handfuls of these subsequences, computational approaches can be employed to tackle the tremendous challenge of understanding this data and providing key biological observations. In this talk, I will describe ultraconserved elements, some of the most perplexing regions within the human genome, and track down a phenomenon of turning genomic junk into gold. The talk will assume no prior knowledge in Molecular Biology
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Hashing Searching Sketching.
Google engEDU
1 hr 2 min – Nov 20, 2006

Google Tech Talks
November 20, 2006

ABSTRACT
We will see improved results on search using hashing and sketching. Hashing is often analyzed as balls being thrown into bins where you think of the hash items as balls and buckets as bins. By studying variants of the balls and bins processes we obtain a hashing algorithm with 85% hash table space utilization. We will also study locality sensitive hashing, a hashing method used for nearest neighbor search, as opposed to exact search. A locality sensitive hash function is likely to map nearby elements to the same bucket. We will see a variant of locality sensitive hashing that finds an approximate nearest neighbor in high dimensions using linear space. We will also see some lower bounds and applications to kd trees.
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Prospects for extending healthy life – a lot
Google engEDU
1 hr 1 min – Jun 1, 2007

Google Tech Talks
May 29, 2007

ABSTRACT

It may seem premature to be discussing approaches to the effective elimination of human aging as a cause of death at a time when essentially no progress has yet been made in even postponing it. However, two aspects of human aging combine to undermine this assessment. The first is that aging is happening to us throughout our lives but only results in appreciable functional decline after four or more decades of life: this shows that we can postpone the functional decline caused by aging arbitrarily well without knowing how to prevent aging completely, but instead by increasingly thorough molecular and cellular repair. The second is that the typical rate of refinement of dramatic technological breakthroughs is rather reliable (so long as public enthusiasm for them is abundant) and is fast enough to change such technologies (be they in medicine, transport, or computing) almost beyond recognition within a natural human lifespan. In this talk I will explain, first, why (presuming adequate funding for the initial preclinical work) therapies that can add 30 healthy years to the remaining lifespan of healthy 55-year-olds may arrive within the next few decades, and, second, why those who benefit from those therapies will very probably continue to benefit from progressively improved therapies indefinitely and thus avoid debilitation or death from age-related causes at any age.

Speaker: Aubrey de Grey Ph.D

Slides available at http://www.sens.org/Google.ppt
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Using Statistics to Search and Annotate Pictures
Google engEDU
56 min – Sep 25, 2006

Google Tech Talks
September 25, 2006

Nuno Vasconcelos is an Assistant Professor at the Electrical and Computer Engineering Department of the University of California, San Diego, where he heads the Statistical Visual Computing Laboratory. Before joining UCSD, he was a member of the research staff at the Compaq Cambridge Research Laboratory, which later became the HP Cambridge Research Laboratory. He received a PhD from MIT in 2000 and his areas of research interest are computer vision, statistical signal processing, machine learning, and multimedia. He is the recipient of a 2005 NSF CAREER award, and a Hellman Fellowship.

ABSTRACT
The last decade has produced significant advances in content-based image retrieval, i.e. the design of computer vision systems for image search. I will review our efforts in the area, with emphasis on the subject of semantic retrieval. This consists of learning to annotate images, in order to support natural language queries. In particular, I will argue for a retrieval framework which combines the best properties of classical "query by visual example" (QBVE), and more recent semantic methods, and which we denote as "query by semantic example" (QBSE). While simple, we show that, when combined with ideas from multiple instance learning, this framework can be quite powerful. It improves semantic retrieval along a number of dimensions, the most notable of which is generalization (out-of-vocabulary queries). It can also be directly compared to query by example, making it possible to quantify the gains of representing images in semantic spaces. Our results show that these gains are quite significant, even when the semantic characterization is noisy and somewhat unreliable. This suggests an interesting hypothesis for computer vision: that it may suffice to adopt simple visual models, as long as they operate at various levels of abstraction and are learned from large amounts of data.
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• Download: “Using Statistics To Search And Annotate Pictures” (video/mp4)

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